Analysis of Bathymetry Data for Shape Prediction of a Reservoir

Shelke, Sushama; Balan, Selva

doi:10.1007/978-981-10-1675-2_10

Cited by 1 publication

(1 citation statement)

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“…From the results obtained, the assumption that depth is strongly related to shoreline distance is verified [HOLLISTER, MILSTEAD 2010]. This shows a high shape regularity of the investigated reservoir, apart the four excluded, in according with SHELKE and BALAN [2017]. The estimated volumes are compared to the actual volumes for a sample of reservoirs.…”

Section: Discussionmentioning

confidence: 62%

Journal of Water and Land Development

Giambastiani,

Giusti,

Cecchi

et al. 2020

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Following flood events and cloudbursts alternating with long drought periods, interest grew in the reservoirs, lakes and water basins in the Tuscany region. In-depth studies are needed to understand the role of water bodies in territorial resilience to climate change. Water volume is the main information to be collected to quantify and monitor their capacity. In this study, a methodology was developed for the estimation of water volume, based on depth measurements taken by sensors with low detection time and costs that can quantify the resource on a regional scale. The depth measuring instrument was a portable sounder with 95 satellite positioning system (Deeper Smart Sonar PRO + (WI-FI + GPS). 204 water bodies were measured. The results indicate that depth is a fundamental parameter to be detected in the field, to obtain the volume with automatic and precise tools. The calculated volume correlates well with the real volume with an R 2 = 0.94. Elaboration of the results led to a model being developed to estimate the volume, knowing only the lake surface area. The database created can be used to conduct future studies on the dynamics of water resources in relation to climate change. It will also be possible to make comparisons with data obtained from satellite and LiDAR (light detection and ranging) surveys.

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Section: Discussionmentioning

confidence: 62%